| Our research focuses on the production of high value-added products such as gasoline, diesel and aviation fuel from plastic waste, which is currently a major environmental challenge. The aim is to develop catalysts with high selectivity and activity for high value added products. We have synthesised and investigated catalysts using various metals and supports and have recently published that reactivity can be enhanced by inducing strong metal-support interactions and controlling the structure of the Ru metal through the addition of triethanolamine (TEA). Research is currently ongoing to identify the active sites of hydrogenolysis and hydrocracking reactions to elucidate the mechanism of the reactions. We conduct basic and applied research to develop catalysts that are environmentally friendly.
- Ro and Co-workers, "Investigating the influence of Ru structures and supports on hydrogenolysis of polyethylene plastic waste", Chemical Engineering Journal. 2023 475, 146076 - Ro and Co-workers, "Investigating the impact of TiO2 crystalline phases on catalytic properties of Ru/TiO2 for hydrogenolysis of polyethylene plastic waste", Environmental Pollution. 2023 121876 -Ro and Coworkers, "Strategic use of thermo-chemical processes for plastic waste valorization", Korean Journal of Chemical Engineering. 2023 40, 693 |
| Our research synthesizes single atom supported catalysts and modifies the structure of the catalysts by controlling the electronic structure of the metal to evaluate their performance for various reactions. We evaluate the reactivity and utilize various analytical techniques to determine the effects of catalyst structure changes, and based on this, we study changes in reaction mechanisms and activation energies. Through various experiments, we aim to synthesize optimal single atom catalysts for specific reactions.
Publications - Ro et al., "Bifunctional hydroformylation on heterogeneous Rh-WOx pair site catalysts ", Nature. 2022, 609, 287 - Ro and Co-workers, "Enhanced Stability of Atomically Dispersed Pd Catalysts via Ionic Liquid Layer Deposition for Selective Acetylene Hydrogenation to Ethylene in Excess Ethylene ", ChemCatChem. 2023 15, e202201428 (Cover features) |
| The conventional catalyst development and research process is an inefficient, labor-intensive, and time-consuming way of working due to Iterative trial and error. In the 4th Industrial Revolution, machine learning using big data has impacted many fields of research, especially the catalytic performance through the combination of machine learning. For catalysis, which has been studied for a long time, there is enough data to apply machine learning to predict catalysts with high activity. In the future, we would like to go beyond predicting the activity of catalysts by combining machine learning with kinetic studies to understand the mechanism of catalyst operation.
Publications - Ro and Co-workers, "Interpretable machine learning framework for catalyst performance prediction and validation with dry reforming of methane", Applied Catalysis B. 2024 343, 123454 - Ro and Co-workers, "Hybrid Quantum Neural Network Model with Catalyst Experimental Validation: Applicaton for the Dry Reforming of Methane", ACS Sustainable Chem. Eng. 2024 in press - Ro and Co-workers, "Accelerating active catalyst discovery: a probabilistic prediction-based screening methodology with applications in dry reforming of methane", Journal of Materials Chemistry A. 2024 12, 1629 |
| Our research focuses mainly on the Dehydrogenation process of liquid organic hydrogen carriers (LOHC), with the goal of utilizing it for the development of reliable hydrogen storage and transportation technologies. Catalysts are synthesized using platinum metal groups (PMGs) and various supports, and their performance is evaluated through experimental tests and theoretical analysis. we aim to improve our understanding of the reaction mechanism. We also work to identify the active sites of the catalysts and explore the structural influence of the catalysts. In essence, we conduct fundamental research to optimize the utilization and performance of catalysts. |
